A path planning method for robot patrol inspection in chemical industrial parks

Safety patrol inspection in chemical industrial parks is a complex multi-objective task with multiple degrees of freedom.Traditional pointer instruments with advantages like high reliability and strong adaptability to harsh environment,are widely applied in such parks.However,they rely on manual readings which have problems like heavy patrol workload,high labor cost,high false positives/negatives and poor timeliness.To address the above problems,this study proposes a path planning method for robot patrol in chemical industrial parks,where a path optimization model based on improved iterated local search and random variable neighborhood descent(ILS-RVND)algorithm is established by integrating the actual requirements of patrol tasks in chemical industrial parks.Further,the effectiveness of the model and algorithm is verified by taking real park data as an example.The results show that compared with GA and ILS-RVND,the improved algorithm reduces quantification cost by about 24%and saves patrol time by about 36%.Apart from shortening the patrol time of robots,optimizing their patrol path and reducing their maintenance loss,the proposed algorithm also avoids the untimely patrol of robots and enhances the safety factor of equipment.

A multi-UAV deployment method for border patrolling based on Stackelberg game

To strengthen border patrol measures, unmanned aerial vehicles(UAVs) are gradually used in many countries to detect illegal entries on borders. However, how to efficiently deploy limited UAVs to patrol on borders of large areas remains challenging. In this paper, we first model the problem of deploying UAVs for border patrol as a Stackelberg game. Two players are considered in this game: The border patrol agency is the leader,who optimizes the patrol path of UAVs to detect the illegal immigrant. The illegal immigrant is the follower, who selects a certain area of the border to pass through at a certain time after observing the leader’s strategy. Second, a compact linear programming problem is proposed to tackle the exponential growth of the number of leader’s strategies. Third, a method is proposed to reduce the size of the strategy space of the follower. Then, we provide some theoretic results to present the effect of parameters of the model on leader’s utilities. Experimental results demonstrate the positive effect of limited starting and ending areas of UAV’s patrolling conditions and multiple patrolling altitudes on the leader ’s utility, and show that the proposed solution outperforms two conventional patrol strategies and has strong robustness.

A cloud Bayesian network approach to situation assessment of scouting underwater targets with fixed-wing patrol aircraft

The battlefield situation changes rapidly because underwater targets'are concealment and the sea environment is uncertain.So,a great number of situation information greatly increase,which need to be dealt with in the course of scouting underwater targets.Situation assessment in sea battlefield with a lot of uncertain information is studied,and a new situation assessment method of scouting underwater targets with fixed-wing patrol aircraft is proposed based on the cloud Bayesian network,which overcomes the deficiency of the single cloud model in reasoning ability and the defect of Bayesian network in knowledge representation.Moreover,in the method,the cloud model knowledge deal with the input data of Bayesian network reasoning,and the advantages in knowledge representation of cloud theory and reasoning of Bayesian network are applied;also,the fuzziness and stochasticity of cloud theory in knowledge expression,the reasoning ability of Bayesian network,are combined.Then,the situation assessment model of scouting underwater targets with fixed-wing patrol aircraft is established.Hence,the directed acyclic graph of Bayesian network structure is constructed and the assessment index is determined.Next,the cloud model is used to deal with Bayesian network,and the discrete Bayesian network is obtained.Moreover,after CPT of each node and the transformation between certainty degree and probability are accomplished;the final situation level is obtained through a probability synthesis formula.Therefore,the target type and the operational intention of the other side are deduced to form the battlefield situation.Finally,simulations are carried out,and the rationality and validity of the proposed method are testified by simulation results.By this method,the battlefield situation can be gained.And this method has a wider application range,especially for large sample data processing,and it has better practicability.

Determination of Main Design Indicators of Patrol Road in Nature Reserves

In principle,nature reserves are managed and controlled according to the core area and the general control area.At present,there is no relevant design specification for the design system of patrol road in various protected areas.This paper analyzed the factors to be considered in determining the grade,horizontal and vertical design indicators,and cross section indicators of the patrol road in the protected area,and came up with the corresponding design indicators and parameters,so as to provide a certain reference for the subsequent patrol road design.

Do Observations during Patrolling Trips Detect Changes in Wildlife Presence & Diversity in National Parks?

Globally, mountains encompass spectacular landscapes and a great diversity of species. However, Savannah’s mountains in Sudan have been affected by the loss of diversity due to human activities and climate changes. Therefore, this study aims to assess changes in wildlife diversity in Jebel-Eldair Nation Park (JENP) based on only reports from patrolling activities, especially in the absence of regular wildlife monitoring programs. Reports of monthly wildlife observations during patrolling trips were used for the summer season in 2010 and 2018. Findings showed a moderate to high decline in the most important wildlife species (i.e. lion, wild dog, and crest porcupine). Six others are documented as rare species in reserve, including the civet, spotted hyena, striped hyena, jackal, seraval, and Siberian bird. Contrary and despite the diversity reduction, some species witnessed increases in their observation frequency, such as lesser kudu, caracal, monitor, and lunar bird. Moreover, human settlements, agricultural activities, and other anthropogenic factors were found to be the main drivers of biodiversity reduction in JENP. The study recommends adopting this method to detect changes in wildlife communities, especially in a situation of deficiency and lack of funding to conduct regular monitoring programs.

A Survey of Multi-robot Regular and Adversarial Patrolling

Multi-robot systems can be applied to patrol a concerned environment for security purposes.According to different goals,this work reviews the existing researches in a multi-robot patrolling field from the perspectives of regular and adversarial patrolling.Regular patrolling requires robots to visit important locations as frequently as possible and a series of deterministic strategies are proposed,while adversarial one focuses on unpredictable robots’moving patterns to maximize adversary detection probability.Under each category,a systematic survey is done including problem statements and modeling,patrolling objectives and evaluation criteria,and representative patrolling strategies and approaches.Existing problems and open questions are presented accordingly.

Research on the Anomaly Detection Method in Intelligent Patrol Based on Big Data Analysis

The network anomaly detection in intelligent patrol is based on the trigger of a single threshold of network element performance parameters in patrol task, which has a high false alarm rate and low efficiency. In order to effectively and accurately integrate network performance, this paper proposes to mine network element performance data and network element log information in the integrated automatic patrol to detect network anomalies. Because log files have a large amount of data and a variety of types, and log data has a complex structure and contains large implied information. The relationship between network anomalies and time can actively discover through the analysis of the log files. Therefore, big data mining and classification can greatly improve the efficiency of data processing. However, the accuracy of finding network anomalies is insufficient only for log analysis. Therefore, this paper puts forward the performance indexes collected in the log analysis and patrol inspection system and adopts the sequence analysis algorithm to detect network anomalies, so as to improve the accuracy and efficiency of detection.

Panda Patrols on the Qinling Mountains

THE Zhouzhi County Laoxiancheng Nature Reserve at the southern foot of the Qinling Mountains in Shaanxi Province is habitat to more than 30 giant pandas. They are looked upon as China’s national treasure. Covering a total area of 12,611 hectares, the nature reserve is also home to other wildlife species, such as antelopes, golden monkeys, and leopards.A patrol of 11 members, formed 15 years ago, works to protect animals living on the reserve, and their natural environment. Each month it spends 3 to 5 days on three inspections. In the 1980s the patrol rescued and treated an injured giant panda they found on the mountain.

NISSAN PATROL 铁汉柔情

途乐是一款具有历史的车型，1951年第一代日产Patrol途乐4W60诞生，至今已经有64年历史，而现款途乐则是在2010年正式发布，发布地点则选择了纸醉金迷的阿联酋迪拜，从这点就可以看出，日产不仅仅希望途乐是那个频繁出现在联合国维和部队画面中，任劳任怨，永远不知疲倦的工具车辆，更是一款足够豪华的高端SUV。

BMC为强化服务级别管理业务推出PATROL for SLM

2000年11月13日美国拉斯维加斯讯——BMC软件公司今天宣布推出针对服务级别管理(Service Level Management【SLM】)的PATROL，这是一个基于PATROL产品线的解决方案，可作为监视和管理服务级别的标准。PATROL FOR SLM从顾客角度审视服务级别管理，可加速对服务级别协议(SLA)的制订和管理，促使企业系统地对其关键业务应用程序的可用性和性能进行优化处理。

赶在烦扰之前——BMC全面电子商务系统管理方案PATROL 2000

在新的网络经济环境下,服务速度与质量成为企业生存发展的关键,企业IT系统的高可用性和快响应速度成为企业服务的速度与质量的保证。在电子商务环境中,当企业业务发展超出预料的速度时,以什么为依据判断IT系统的性能是否正常?系统需做出明陛改善以适应发展?如何有效管理电子商务环境,使之成为电子商务顺利进行的重要保障?

PATROL UPLC巡查过程分析仪

2008年匹茨堡大会上，沃特世公司隆重推出PATROL^TM UPLC^TM过程分析仪，一种实时的液相色谱（LC）在线分析技术（PAT）系统，可以在生产线检测和定量多组分生产样品和最终产品。

基于混合遗传算法的多无人机巡逻路径优化

假设无人机巡逻的起、终点均为派出所,提出了一种融合传统遗传算法和爬山算法的警用无人机巡逻路径优化模型——混合遗传算法。按照轮盘赌法则,进行种群个体的选择,以增大优秀种群个体被选中的概率,达到较好的优化效果。同时定义了与路径优化相适应的基因交叉和变异规则。仿真结果表明,提出的混合遗传算法在寻优效果上明显优于传统遗传算法。

深化高校巡视巡察成果运用的路径研究

习近平总书记强调,巡视发现问题的目的是解决问题,发现问题不解决,比不巡视的效果还坏[1]。巡视巡察成果运用是深化推动解决问题的关键环节,只有不断强化成果运用的深度、广度和力度,方能实现监督、整改、治理有机贯通。本文在把握巡视巡察成果运用趋势的基础上,基于对北京高校的实证分析,以“四个融入”为核心设计了高校巡视巡察成果运用路径,系统构建了责任落实机制、约谈通报机制、公开考评机制和追责问责机制,为推进高校巡视巡察成果的综合运用、深化运用提供了参考范式。

京沪高铁基础设施无人机智能巡检系统关键技术

近年来我国高速铁路建设里程不断增长,传统巡检技术与方式无法满足日益增长的高铁运行安全保障需求。同时,基于无人机的解决方案已在电力、水利及城市监测等领域投入使用并取得较好效果。开展无人机在高速铁路智能巡检应用方面的关键技术研究,提出高速铁路基础设施无人机综合巡检方案,具体包括:基于无人机搭载多类型传感器的无人机巡检系统构成方案,基于深度学习的声屏障异常检测方法、周边环境异常检测方法、铁路桥梁螺栓缺失及锈蚀检测方法、接触网紧固件缺陷检测方法等;基于上述方案的智能巡检系统在京沪高铁多个区段进行试验验证,结果表明:该系统可以有效检测铁路多专业中的多类缺陷,并与现有巡检方法形成互补,从而提升铁路运行安全保障水平,为无人机铁路巡检技术的大范围应用提供参考。

基于改进YOLOv5s的输电线路螺栓缺销检测方法

针对无人机输电线路巡检图像中螺栓缺销检测精度较低、漏检较多的问题,提出了一种基于改进YOLOv5s的输电线路螺栓缺销检测方法。在Backbone部分嵌入Coordinate Attention注意力模块;在Neck部分原有的“FPN+PAN”结构的基础上,新增一条“自顶向下”的特征信息传递路径,跨越临近的同尺度特征层,与较浅层网络以加权融合的方式进行特征融合;将Head部分设置为解耦检测头,将对螺栓检测的分类任务与定位任务分开进行。改进后的YOLOv5s算法增强了对螺栓特征信息的学习能力。使用本方法在螺栓缺销数据集上实验,精确率提升了2.3%,召回率提升了3.4%,平均精度提升了3.1%,检测速度达到了41.1帧/秒,表明改进后的方法能提升输电线路螺栓缺销的检测能力,在智能巡检中具有一定的应用价值。

数字孪生水利工程建设动态智能监测系统研发与应用

依托大型水利枢纽工程建设,结合项目进度、质量、安全等管理要求,提出数字孪生水利工程动态智能监测系统研发思路。通过研究水下定位和水陆一体化定位,建立水下机器人与无人机智能巡检的统一定位体系;研究海量影像数据存储管理,研究图像识别和机器学习技术自动找出异常点,从而实现施工现场的智慧监控等关键技术。建成集空、天、地、水一体化的监控系统,对各项感知信息进行融合集成和综合利用,对不同时期的数据进行比较分析;建立大数据平台,为大型水利工程设计、工程移民、水土保持、施工安全与质量管理、工程形象展示、水下建筑物安全监测等方面的数字孪生水利工程建设和动态监测提供技术支持,实现大型水利枢纽工程建设过程的智能巡检、智能监测和科学监管。

改进粒子群算法的机器人避障偏差控制方法

为针对巡检机器人避障偏差进行良好控制,提升避障效果,提出改进粒子群算法的机器人避障偏差控制方法设计。先分析巡检机器人正向动力学和逆向动力学,获取双走轮坐标系下机器人的运动情况,建立机器人运动学方程。然后以此为基础,在双走轮坐标系中,通过改进粒子群算法确定巡检机器人全局避障最优路径,采用改进人工势场法完成局部避障路径规划,最后采用前馈补偿控制器为动力学方程和最优路径建立动态补偿,根据控制器输出的训练结果,实现巡检机器人避障偏差自动控制。实验结果表明:所提方法避障规划能力及避障运动控制能力均较强,避障偏差控制效果好,具有一定应用价值。